Files
chart-sins/docs/content-backlog.md
T
Claude 761e048811 Work the five delivered sources into the pages
The source-request loop paid for itself immediately — two of the five
corrected something rather than confirming it.

The Economist piece settles V1, the riskiest live claim, but our note
had over-claimed: truncating the scale is its *first* example, not one
of "several." Note rewritten to quote her. The same article turned out
to contain a dual-axis chart she caught herself on, now cited.

Datawrapper's color-scale part 1 refuted the assumption behind a queued
sin outright: it makes no argument against rainbow scales and endorses
multi-hue sequential gradients. The rainbow entry is now marked as
having no verified source at all, rather than ample backing.

The dual-axis post independently draws the same line we drew last turn
— of four uses only the alternative-scale case survives, their example
being F against C — and led to two references worth more than the blog
post: the Isenberg et al. study that tested dual-scale charts, and Few's
article working through the cases. Both ship without full metadata
rather than guessed metadata; queued.

Pie and stacked posts gave verbatim support, plus one correction: a
100%-stacked chart has two readable baselines, not one.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ULE5RRxdQE1ebwefEd2eCM
2026-08-05 17:37:47 +00:00

11 KiB
Raw Blame History

Content backlog — what to write next

Working document. Ranked by what is worth writing — the sins people actually commit, and the pages most worth sending someone.

Sourcing is a constraint on that list, not the thing that generates it: a sin earns a slot because it's worth a page, and then we go find the sources that make the case. Never the reverse. What we don't do is invent authority, or stretch a source into saying something it doesn't.

The list deliberately mixes registers. Some sins are subtle enough that a competent analyst commits them by accident; others are arithmetically void and indefensible on sight. Both belong — the egregious ones are the most sendable pages we can write, because there's nothing to argue about, and the subtle ones are what keep the site useful to people who already know the basics. Severity runs 25 on purpose.

Sources in play

src/lib/references.ts currently holds 24 entries, 20 of them cited by the five published sins. This table is a convenience, not a scoreboard — it's here so you can spot a source that fits a sin you're drafting, not so we can drive the right-hand column to zero blanks. An uncited reference is not a debt.

Adding new references is the normal way to strengthen a page. If a sin deserves seven sources, give it seven and add whatever's missing to the file.

Reference Cited by
ftvisvocab
healy
munzner
schwabish
fewdualaxes dual-axis-correlation
fewpies too-many-pie-slices
huff truncated-y-axis
isenberg2011 dual-axis-correlation
shapeparameter aspect-ratio
showmenumbers too-many-pie-slices
spurious dual-axis-correlation
swd dual-axis-correlation
tufte truncated-y-axis
vizwtf inverted-y-axis
callingbullshit inverted-y-axis, truncated-y-axis
datatoviz dual-axis-correlation, too-many-pie-slices
datawrapper dual-axis-correlation, too-many-pie-slices
eagereyes aspect-ratio, too-many-pie-slices
junkcharts inverted-y-axis, too-many-pie-slices
truthfulart aspect-ratio, dual-axis-correlation
wilke too-many-pie-slices, truncated-y-axis
clevelandmcgill aspect-ratio, too-many-pie-slices, truncated-y-axis
economistmistakes dual-axis-correlation, inverted-y-axis, truncated-y-axis
howchartslie aspect-ratio, dual-axis-correlation, inverted-y-axis, truncated-y-axis

The citation lists in each entry below are starting points, not budgets — add to them while drafting.

Ranked backlog

1. A Cherry-Picked Time Range — Deceptive Framing, severity 5

Poke: "You started the clock exactly where the story got good."

The trend runs one way over five years and the other way over five months, so the chart shows the five months. Nothing about the chart is technically false — the axis starts at zero, the labels are honest — which is what makes it the nastiest sin on this list.

Charts: one series, two views. Bad = the flattering slice. Fixed = the full record with the slice shaded in place. Literally the same dataset filtered, so the "same numbers, both charts" rule holds by construction — the strongest proof we can build.

Citations: huff (the original con), callingbullshit, howchartslie, junkcharts.

2. Pie Slices That Sum to More Than 100% — Impossible Wholes, severity 5

Poke: "Your slices add up to 180%. A pie has one job — dividing a whole — and this data has no whole to divide."

The multi-select survey is the classic source: "which of these tools do you use?", respondents tick three each, and the results get poured into a pie. The wedges are now sized as fractions of a total that doesn't exist, so every one of them is drawn wrong, and the "share" each appears to hold is pure artifact.

Unlike most of this list, there's no judgment call — the chart is arithmetically void. That's the appeal: nothing to argue about, and no way to defend it in a meeting.

Charts: bad = pie of multi-select response counts, wedges summing past the circle. Fixed = bar chart, one bar per option, each labelled "% of respondents" with the base stated. Same counts.

Citations: fewpies, datawrapper — but only for the premise: their pie-chart post says "one pie chart can only show one total and its shares," and it does not separately argue that parts must be mutually exclusive. Don't stretch it further than that. Plus datatoviz, junkcharts.

3. A Pie Chart of Rates or Averages — Impossible Wholes, severity 5

Poke: "You made a pie out of averages. Adding them together produces a number that means nothing, and that number is your denominator."

The other half of the same mistake, and the one people defend for longer. Average deal size by region, conversion rate by channel, satisfaction score by team — relative metrics, each with its own denominator, stacked into wedges as if they were parts of a shared total. A region with a high average takes a big slice regardless of how many deals it actually did.

Worth its own page rather than folding into the entry above: the tell is different (these numbers can sum to 100% by coincidence), and the person who needs sending here is making a different error — a category mistake about what their metric is, not a counting mistake.

Charts: bad = pie of average order value by region. Fixed = bar chart of the same averages, plus the volume behind each one so the weighting is visible.

Citations: fewpies, munzner (part-to-whole is a composition of a whole, or it is nothing), datawrapper (same one-total premise as above), schwabish, ftvisvocab.

4. Group Averages Shown Without the Distribution — Hiding the Data, severity 4

Poke: "Four bars, four averages, and no idea whether the difference is real."

The bar-of-means: every group collapsed to one number, so wildly different distributions draw identical bars. Wilke devotes a section to exactly this and Healy makes the perceptual case.

Charts: bad = grouped bar of means. Fixed = strip/box plot over the same observations, means still marked.

Citations: wilke, healy, schwabish, datatoviz.

5. Bubbles Sized by Radius Instead of Area — Perceptual Traps, severity 4

Poke: "You doubled the number and quadrupled the ink."

Scaling a circle's radius by the value instead of its area squares the apparent difference. This is Tufte's Lie Factor with an actual number attached, and Munzner's channel ranking — already underwriting the pie and truncated-axis sins — applies directly.

Charts: bad = radius ∝ value (a calculate transform squaring the size encoding). Fixed = area ∝ value, or better, the same values as a dot plot where position does the work.

Citations: munzner, clevelandmcgill, tufte, howchartslie.

6. Stacked Segments Without a Shared Baseline — Perceptual Traps, severity 3

Poke: "Only the bottom band of a stacked chart has a straight edge to measure against. The rest are guesses."

In a stacked column chart, every segment except the bottom one starts at a baseline that moves from column to column. Datawrapper puts it plainly: "It's hard for readers to compare columns that don't start at the same baseline," and their fix is to "bring the most important value to the bottom of the chart."

One correction to how I first framed this, from reading their post: a 100%-stacked chart has two readable baselines, not one — the top edge works as well as the bottom. So the sin isn't "only the bottom is readable," it's that everything between the two baselines floats. Write it that way; adjust the poke accordingly.

Ubiquitous in business dashboards, which is what earns it a slot despite the milder severity. The Economist's own rainbow-stack example is a good second angle: they stacked a selection of euro-area countries, and stacking implies the parts are the whole.

Charts: bad = stacked columns with the interesting series stranded in the middle. Fixed = the same numbers as small multiples (or the key series pulled out to its own zero baseline), totals preserved.

Citations: datawrapper, wilke, munzner, ftvisvocab.

7. Categories Sorted Alphabetically Instead of by Value — Sloppy Craft, severity 2

Poke: "Your categories are sorted by name. Nobody wants to know which region starts with A."

Venial, universal, and the single most useful page to fire at a colleague — which is the whole product thesis. Low severity is a feature: the gallery needs a range.

Charts: bad = categorical bars in alphabetical order. Fixed = same bars sorted by value.

Citations: schwabish, ftvisvocab, swd, fewpies.

Not yet buildable

Real sins, but our pipeline can't prove them honestly today. Recorded so we stop rediscovering them:

  • 3D bars / gratuitous perspective and chartjunk (Tufte, Few) — Vega-Lite won't render the sin, and a screenshot violates the same-pipeline rule that makes the before/after credible.
  • Counts on a choropleth instead of rates (Cairo's set-piece) — needs TopoJSON geometry and a build-time data dependency we don't have yet. Strong candidate the moment we take that on.
  • Rainbow color scales for continuous data — blocked on both counts, and I had this wrong before. Part 1 of Datawrapper's color series turned out to be a taxonomy that makes no argument against rainbow scales at all, and it explicitly endorses multi-hue sequential gradients (see docs/sources/datawrapper-color-scales.md). So we currently have no verified source for the rainbow critique — parts 24 and Kosara's "How The Rainbow Color Map Misleads" are queued. The palette work is still outstanding too: the fixed chart needs a sequential ramp validated on --chart-canvas in both themes. Don't draft this one until a real source is in hand.

Conventions reminder

Note what the two pie entries above do and don't say. Neither condemns the pie chart — both condemn feeding one data that has no whole to divide. Same for a second y-axis: the form is fine, the manufactured correlation is not. We don't ban chart types here, and a backlog entry that reads like a blanket ban has been written wrong. See the severity rubric in CLAUDE.md — a form with legitimate uses caps out at 4.

Anything picked up from this list still follows CLAUDE.md: the title names the problem plainly and leaves the wit to the poke, the poke names the general sin and never our sample's numbers, both charts share one dataset, and the fixed chart obeys every rule the site preaches.

The headings above are working titles written to that rule — they say what the sin is, so they can be taken as-is or rephrased without having to first decode a pun.